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Training - Courses

MLPR: MATLAB Programming Techniques

MATLAB Programming Techniques provides hands-on experience using the features in the MATLAB® language to write efficient, robust, and well-organized code. These concepts form the foundation for writing full applications, developing algorithms, and extending product capabilities. Details of performance optimization are covered throughout the course, as well as tools for writing, debugging, and profiling code.

Topics include:

  • Programming for correctness
  • Structuring data
  • Structuring code
  • Classes and objects
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 Detailed course outline

 

Day 1 of 1
Introduction

Objectives:

  • Obtain a quick overview of The MathWorks and MATLAB
  • Discuss course set-up, materials, and logistics
  • Provide a “big picture” view of the course ahead
Programming for Correctness

Objective: Creating robust applications that withstand unexpected input and produce meaningful errors is the goal of many application developers. Through the use of built in MATLAB functions and programming constructs, this section covers standard techniques for handling error conditions. Tools for debugging code, diagnosing problems, and measuring performance are an integral part of this section.

  • Warnings and errors
  • Handling errors
  • The try-catch construct
  • The MException object
  • Analyzing code in the MATLAB Editor
  • Directory reports
  • MATLAB Debugger
  • Assessing performance
  • MATLAB Profiler
Structuring Data

Objective: This section examines choices for storing data within a MATLAB application. The choice of data type plays an important role in an application's storage requirements and execution time. Highlighted in this section are common techniques for improving performance when storing, accessing, and processing data.

  • Cell arrays
  • Structure arrays
  • Other data containers
  • Preallocation
  • Vectorization
  • Memory management
  • Passing data between functions
Structuring Code

Objective: Modularizing code into readable and maintainable functions is often an important design consideration. This section explores the different function types available in the MATLAB language, and discusses some of the tradeoffs associated with these choices. The effect of the function type on performance, as well as reliability of the code, is an important theme throughout the chapter.

  • Private functions
  • Function handles
  • Subfunctions
  • Nested functions
  • Precedence rules
  • Variable scope and visibility
  • Comparison of function types
Classes and Objects

Objective: This section of the course discusses an approach for combining data and its associated operations into a custom data type, or class. By writing classes, and creating objects from those classes, this section shows simple techniques used in advanced application development. Custom classes form the foundation for organizing large applications.

  • Class definition files
  • Properties
  • Property attributes
  • Methods
  • Creating object instances
  • Handle classes
  • Overloading operators
  • Precedence rules

Prerequisites

MATLAB Fundamentals, or equivalent experience using MATLAB and familiarity with basic programming concepts

Course Length - 1  day

Price - £500.00

Please Note: Course price does not include VAT

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